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§6.1: I do not understand why for nested theories they do not use BIC, but instead a likelihood-ratio test (which ignores nr. of parameters). %}
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Conte, Anna & John D. Hey (2013) “Assessing Multiple Prior Models of Behaviour under Ambiguity,” Journal of Risk and Uncertainty 46, 113–132. {% %} Conte, Anna, John D. Hey, & Peter G. Moffatt (2011) “Mixture Models of Choice under Risk,” Journal of Econometrics 162, 79–88. {% Time pressure enhances irrationality. %} Conte, Anna, Marco Scarsini, & Oktay Sürücü (2016) “The Impact of Time Limitation: Insights from a Queueing Experiment,” Journal of Behavioral Decision Making 11, 260–274. {% dynamic consistency: people rather have a strong electric shock immediately than weaker shock with eight seconds delay, in order to avoid anxiety. %} Cook, John O. & Lehman W. Barnes, Jr. (1964) “Choice of Delay of Inevitable Shock,” Journal of Abnormal and Social Psychology 68, 669–672. {% %} Cook, Philip J. & Daniel A. Graham (1977) “The Demand for Insurance and Protection: The Case of Irreplaceable Commodities,” Quarterly Journal of Economics 91, 143–156. {% Methoden & Technieken; have nice figs of QED; discusses various forms of validity. %} Cook, Thomas & Donald E. Campbell (1979) “Quasi-experimentation, Design and Analysis Issues for Field Settings.” Rand McNally, Chicago. {% Arne, Thom %} Cook, Wade D. & Moshe Kress (1987) “Tournament Ranking and Score Difference,” Cahiers du C.E.R.O. 29, 215–222. {% %} Cooke, Nancy J., Robert S. Atlas, David M. Lane, & Robert C. Berger (1993) “Role of High-Level Knowledge in Memory for Chess Positions,” American Journal of Psychology 106, 321–351. {% %} Cooke, Roger M. (1987) “A Theory of Weights for Combining Expert Opinion,” Report 87-25, Department of Mathematics, Delft University of Technology. {% probability elicitation %} Cooke, Roger M. (1988) “Uncertainty in Risk Assessment: A Probabilist’s Manifesto,” Reliability Engineering and System Safety 23, 277–283. {% proper scoring rules; cited by Winkler as standard work on the valuation of experts %} Cooke, Roger M. (1991) “Experts in Uncertainty; Opinion and Subjective Probability in Science.” Oxford University Press, New York. {% They take finite models, such as Savage’s model of decision under uncertainty with, say, 4 states and 4 consequences (and 44 acts = maps from states to consequences). Then they consider ALL binary relations on the acts. They count how many of those satisfy preference conditions, such as how many satisfy transitivity + sure-thing principle. The total nr. satisfying a group of conditions is taken as an index of the restrictiveness of this group of conditions. %} Cooke, Roger M. & Henk Draaisma (1984) “A Method of Weighing Qualitative Preference Axioms,” Journal of Mathematical Psychology 28, 436–447. {% probability elicitation %} Cooke, Roger M., Max Mendel, & Wim Thijs (1988) “Calibration and Information in Expert Resolution; a Classical Approach,” Automatica 24(1), 87–94. {% %} Coombs, Clyde H. (1964) “A Theory of Data.” Wiley, New York. {% %} Coombs, Clyde H. (1987) “The Structure of Conflict,” American Psychologist 42, 355–363. {% %} Coombs, Clyde H., Thom G.G. Bezembinder, & Frank M. Goode (1967) “Testing Expectation Theories without Measuring Utility or Subjective Probability,” Journal of Mathematical Psychology 4, 72–103. {% Maths for econ students. Say somewhere (I got this from George Wu), that the main contribution of the EU axioms is a theoretical justification that is independent of “long-run considerations .. (and) hence ... applicable to unique choice settings.” Teaching book for math. Psych.; math. app. on sets, product sets, eq.rel., ordering, fie, distance fie, matrix-multiplication, permutations, probability discr., total of 39 pp. %} Coombs, Clyde H., Robyn M. Dawes, & Amos Tversky (1970) “Mathematical Psychology, An Elementary Introduction.” Prentice-Hall, Englewood Cliffs, NJ. {% Separate treatment of gaines and losses; %} Coombs, Clyde H. & Lehner, Paul E. (1984) “Conjoint Design and Analysis of the Bilinear Model: An Application to Judgments of Risk,” Journal of Mathematical Psychology 28, 1–42. {% risk seeking for symmetric fifty-fifty gambles: seem to find it. P. 273 seems to suggest that these gambles are liked for being “fair” and easier to understand. %} Coombs, Clyde H. & Dean G. Pruitt (1960) “Components of Risk in Decision Making: Probability and Variance Preferences,” Journal of Experimental Psychology 60, 265–277. {% %} Cooper, William S. (1987) “Decision Theory as a Branch of Evolutionary Theory: A Biological Derivation of the Savage Axioms,” Psychological Review 94, 395–411. {% On ordinal revolution, concentrating on interpersonal comparability of utility. Many nice citations and references. The authors use Pareto’s distinction between utility bringing usefulness and fulfilling needs (in principle objective and observable), and utility fulfilling desires (ophelimity, subjective). They argue that the ordinalists did not bring unambiguous progress in economics but instead changed the meaning of utility from usefulness (ordinal) to desires-fulfilment and changed the domain from welfare evaluation to consumer/price theory. Pre-ordinalists (called “material welfare school” by Cooter & Rappoport) took utility not as revealed through choices, but still observable, by seeing how well a person is doing, usually taken at group level of number of sick people etc. This was taken as in principle objective and observable. Utility means usefulness, probably same as fulfilling needs (“wants”), and is normative/rational. Bad-tasting medicine for child gives usefulness but no ophelimity. (I don’t see the difference, child misjudges desires by overlooking long-term desires. P. 516 footnote 23: Pareto (1896) seems to say that the two concepts should coincide for a rational person. So then ophelimity is descriptive and usefulness is normative?) P. 510: paradox of value (water is more useful than diamonds but we pay less for it) prevented utility to be useful in economics up to around 1870. Jevons (1871) resolved it by considering marginal utility. Describes also the marginalist revolution of utility around 1870, initiated by Jevons. marginal utility is diminishing: many refs and historical citations in diminishing marginal utility. P. 516: “the power of commodities to satisfy material needs was called utility.” P. 520 etc.: big role for Robbins (1932/7) in ordinal revolution. P. 527: “The belief that a utility structure was common to people made introspection an appropriate empirical tool.” I like the many details, but not the main message, of this paper. The ordinalists’ idea to firmly base utility on observed choice was definitely a step forward. Only if ordinalists go too extreme by saying that all other things are useless (“meaningless,” as ordinalists often argue, unfortunately) then they go too far I think. The authors make many distinctions on subtleties in utility, e.g. is it descriptive/normative, is it pleasure- or goal- fulfilling, is it on basic needs (food) or also on more abstract things (theatre, social life), etc. These aspects of interpretation of utility shift between different authors and in general over time, and some aspects are more prominent for ordinalist- than for other utility. I disagree that making distinctions on these details justifies the claim that ordinalists were dealing with completely different questions and concepts. Lyons (1986) may be another reference for history of ordinal revolution. %} Cooter, Robert D. & Peter Rappoport (1984) “Were the Ordinalists Wrong about Welfare Economics?,” Journal of Economic Literature 22, 507–530. {% %} Cooter, Robert D. & Peter Rappoport (1985) “Reply to I.M.D. Little’s Comment,” Journal of Economic Literature 23, 1189–1191. {% %} Copas, John & Dan Jackson (2004) “A Bound for Publication Bias Based on the Fraction of Unpublished Studies,” Biometrics 60, 146–153. {% Beautiful title. %} Copertari, Luis (2009) “Are Praying Useless, Free Will an Illusion and Some Evil Unavoidable?,” working paper. {% %} Corbett, Charles J. & Luk N. van Wassenhove (1993) “The Natural Drift: What Happened to Operations Research?,” Operations Research 41, 625–640. {% %} Corcos, Anne, François Pannequin, & Sacha Bourgeois-Gironde (2012) “Is Trust an Ambiguous rather than a Risky Decision,” Economics Bulletin 32, 2255–2266. {% Use the Epstein-Zin model to analyze it, with aversion to information, preference for timing of resolution of uncertainty, and so on. information aversion: discuss it extensively %} Córdoba, Juan Carlos & Marla Ripoll (2017) “Risk Aversion and the Value of Life,” Review of Economic Studies 84, 1472–1509. {% %} Corner, James L. & Craig W. Kirkwood (1991) “Decision Analysis Applications in the Operations Research Literature, 1970–1989,” Operations Research 39, 206–219. {% ambiguity seeking: They ask subjects in an experiment to price investments with uncertain returns. They induce ambiguity by giving interval info on returns. They do not find any ambiguity aversion. So, they do not find ambiguity seeking, bt neutrality. %} Corgnet, Brice, Praveen Kujal, & David Porter (2012) “Reaction to Public Information in Markets: How Much Does Ambiguity Matter?,” Economic Journal 123, 699–737. {% measure of similarity %} Corter, James E. (1982) “ADDTREE/P: A PASCAL Program for Fitting Additive Trees Based on Sattath & Tversky's ADDTREE Algorithm,” Behavior Research Methods and Instrumentation 14, 353–354. {% revealed preference: the paper suggests that revealed preference theory has been developed for linear budget sets and not for the case where choice sets are finite, but this more important case has often been considered. Only the end of §1.1 very briefly mentions the existence of such literature, and then writes that this paper is intermediate in considering finite choice sets of commodity bundles. %} Cosaert, Sam & Thomas Demuynck (2015) “Revealed Preference Theory for Finite Choice Sets,” Economic Theory 59, 169–200. {% For frequencies, people don’t do so bad; evolutionary reasons also %} Cosmides, Leda & John Tooby (1996) “Are Humans Good Intuitive Statisticians after All? Rethinking Some Conclusions from the Literature on Judgment under Uncertainty,” Cognition 58, 1–73. {% %} Costa-Gomes, Miguel, Steffen Huck, & Georg Weizsäcker (2014) “Beliefs and Actions in the Trust Game: Creating Instrumental Variables to Estimate the Causal Effect,” Games and Economic Behavior 88, 298–309. {% probability elicitation: applied to experimental economics. Paper uses quadratic scoring rule to elicit subjective probabilities in repeated games. The beliefs do not perform well. Calibration and discrimination are not good relative to real play (p. 742, top), and they are inconsistent with players’ own choices. %} Costa-Gomes, Miguel & Georg Weizsäcker (2008) “Stated Beliefs and Play in Normal-Form Games,” Review of Economic Studies 75, 729–762. {% DOI 10.1007/s11083-015-9382-8 This paper mentions the well-known point that decision under uncertainty can be considered to be a special case of multiattribute utility. Then it examines and generalizes the Sugeno integral for the case of different component sets connected through utilituy functions, leading to state-dependent utility for decision under uncertainty. %} Couceiro, Miguel, Didier Dubois, Henri Prade, & Tamas Waldhauser (2016) “Decision-Making with Sugeno Integrals: Bridging the Gap Between Multicriteria Evaluation and Decision under Uncertainty,” Order 33, 517–535. {% %} Cottrell, Allin (1993) “Keynes’s Theory of Probability and its Relevance to His Economics,” Economics and Philosophy 9, 25–51. {% %} Coulhon, Thierry & Philippe Mongin (1989) “Social Choice Theory in the Case of von Neumann-Morgenstern Utilities,” Social Choice and Welfare 6, 175–187. {% %} Coupé, Tom (2003) “Revealed Performances: Worldwide Rankings of Economists and Economics Departments, 1990–2000,” {% ranking economists; tijdschrift onder eigen naam (alfabetisch: J) in boekenkast %} Coupé, Tom (2003) “Revealed Performances: Worldwide Rankings of Economists and Economics Departments, 1990–2000,” Journal of the European Economic Association 1, 1309–1345. {% Introduced his equilibrium. %} Cournot, Antoine Augustin (1838) “Researches on the Mathematical Principles of the Theory of Wealth.” Chez L. Hachette, Paris. {% %} Cournot, Antoine Augustin (1843) “Exposition de la Théorie des Chances et des Probabilités.” Ed.: Bernard Bru, Librairie J. Vin, Paris, 1984. {% Argue that biases and WTP-WTA discrepancy can be solved by practicing, feedback and incentives. %} Coursey, Don L., John L. Hovis, & William D. Schulze (1987) “The Disparity between Willingness to Accept and Willingness to Pay Measures of Value,” Quarterly Journal of Economics 102, 679–690. {% Measure - model. Find that obesity is partly attributable to both discounting () and time inconsistency (). %} Courtemanche, Charles, Garth Heutel, & Patrick McAlvanah (2015) “Impatience, Incentives and Obesity,” Economic Journal 125, 1–31. {% homebias: seems to show that within same country there is a kind of homebias for own region. %} Coval, Joshua D. & Tobias J. Moskowitz (1999) “Home Bias at Home: Local Equity Preference in Domestic Portfolios,” Journal of Finance 54, 2045–2073. {% Show that loss aversion affects prices. Prices in afternoon are often reaction to prices in the morning. %} Coval, Joshua D. & Tyler Shumway (2005) “Do Behavioral Biases Affect Prices?,” Journal of Finance 60, 1–34. {% %} Cowell, Frank A. & Erik Schokkaert (2001) “Risk Perceptions and Distributional Judgments,” European Economic Review 45, 941–952. {% %} Cowen, Tyler & Jack High (1988) “Time, Bounded Utility, and the St. Petersburg Paradox,” Theory and Decision 25, 219–223. {% foundations of statistics; try to argue that Ronald A. Fisher was not the first to propose the .05 level of significance by describing bits and pieces that existed before. After reading it seemed to me that still Fisher is the first who really proposed it. %} Cowles, Michael & Caroline Davis (1982) “On the Origins of the .05 Level of Statistical Significance,” American Psychologist 37, 553–558. {% foundations of statistics. The paradox that he discussed is maybe called John Pratt’s censoring paradox nowadays. P. 358: “… the general point is that prior information that is not statistical cannot be included without abandoning the frequency theory of probability.” P. 367 explains that level of significance etc. should depend on decisions, losses, etc. P. 368 (where (2) is significance): “The advantage of (2) is that it has a clear-cut physical interpretation …” This page also has a good example suggesting that the likelihood ratio is a better measure than significance. “We are faced with a conflict between the mathematical and logical advantages of the likelihood ratio, and the desire to calculate quantities with a clear practical meaning in terms of what happens when they are calculated.” %} Cox, David R. (1958) “Some Problems Connected with Statistical Inference,” Annals of Mathematical Statistics 29, 357–372. {% foundations of statistics %} Cox, David R. (1977) “The Role of Significance Tests.” In Omar F. Hamouda & J.C. Robin Rowley (1997, eds.) “Statistical Foundations for Econometrics.” Edward Elgar, Cheltenham. {% Emphasis on Fisher’s views %} Cox, David R. (1990) “Role of Models in Statistical Analysis,” Statistical Science 5, 169–174. {% foundations of statistics; …. “acceptance and rejection of hypotheses … give certain quantities hypothetical physical interpretations and are not instructive on how to apply the method …” “we may wish to assess procedures that are not in a technical sense optimal either because none such exist or because of considerations such as transparency or robustness. Neyman-Pearson arguments are clearly very fruitful for this.” %} Cox, David R. (1999) “Discussion of Michael D. Perlman & Lang Wu, “The Emperor’s New Tests”,” Statistical Science 14, 373–374. {% foundations of statistics: Personal account of nine important statisticicans. Pp. 747-748 expresses Fisher’s view on mathematical rigor: “Mechanical drill in the technique of rigorouis statement was abhorrent to him, partly for its pedantry, and partly as an inhibition to the active use of the mind.” P. 749 bottom n Harold Jeffrey using probability for objective degree of belief, and chance for physical frequencies. Tversky used “chance” the same way in conversations with me. P. 754 on Savage. Was mathematician influenced much by Wald’s decision-approach. How Anscombe, Lindley, Cox read an early version of foundations of statistics. Cox writes: “I recall finding the book fascinating but ultimately unconvincing, at least as basis of applied statistical work in which I had been involved” P. 755: “Despite the undoubted interest of this [internal consistency] approach, it seems relatively remote from the objectives of much statistical work because it is not sufficiently firmly anchored in the real world.” P. 755: [Wald] sought to cast the whole of statistical theory in decision-theoretic terms. Despite the importance of specific decision-making problems, such as health screening and sampling inspection, most statistical problems, even if they have some decision-making element, do not fit easily into that formulation.” P. 755: “Rather, by probability Fisher meant a proportion in a hypothetical infinite population”. %} Cox, David R. (2016) “Some Pioneers of Modern Statistical Theory: A Personal Reflection,” Biometrika 103, 747–759. {% §2.3 ? (or pp. 33ff) on likelihood principle seems to point out a problem of conditioning on ancillary statistics; p. 38 seems to define the conditionality condition which says that one should condition on an ancillary statistic. %} Cox, David R. & David V. Hinkley (1974) “Theoretical Statistics.” Chapman and Hall, London. {% %} Cox, David R., Ray Fitzpatrick, Astrid E. Fletcher, Sheila M. Gore, David J. Spiegelhalter, & David R. Jones (1992) “Quality-of-Life Assessment: Can we Keep it Simple?,” Journal of the Royal Statistical Society A 155, 353–393. {% %} Cox, James C. & Seth Epstein (1989) “Preference Reversals without the Independence Axiom,” American Economic Review 79, 408–426. {% %} Cox, James C., Daniel Friedman, &Steven Gjerstad (2007) “A Tractable Model of Reciprocity and Fairness,” Games and Economic Behavior 59, 17–45. {% Consider choices from convex compact subsets of Re2, as for instance in bargaining game theory. Interpret it as welfare allocations over two players where one is one-self. They introduce axioms of “more altruistic than,” “more generous than,” and others, and indicate how empirical evidence of known games can test these, relating these to popular current developments in experimental game theory. %} Cox, James C., Daniel Friedman, & Vjollca Sadiraj (2006) “Revealed Altruism,” Econometrica 76, 31–69. {% Second-price auction was run several times. Preference reversals were originally as usually found, but later decreased. %} Cox, James C. & David M. Grether (1996) “The Preference Reversal Phenomenon: Response Mode, Markets and Incentives,” Economic Theory 7, 381–405. {% Discuss Rabin (2000, Econometrica). Point out the relevance of the assumption whether or not people think in terms of final wealth or changes w.r.t. the status quo. They point out that EUI (Expected utility of income, where income is taken as change w.r.t. status quo) is not rejected by Rabin’s points. This is, as far as I can see, in perfect !agreement! with Rabin’s viewpoint because Rabin, and most of the literature, calls EUI “prospect theory” (without probability transformation), in which loss aversion can come into play. %} Cox, James C. & Vjollca Sadiraj (2006) “Small- and Large-Stakes Risk Aversion: Implications of Concavity Calibration for Decision Theory,” Games and Economic Behavior 56, 45–60. {% Criticize Weber’s coefficient of variation (CV) for having unsound properties, such as violations of stochastic dominance, and falsify it in an experiment with real incentives. %} Cox, James C. & Vjollca Sadiraj (2010) “On the Coefficient of Variation as a Criterion for Decision under Risk,” Journal of Mathematical Psychology 54, 387–394. {% random incentive system: test this as well as several other payment schemes, such as PAS (pay all sequentially, immediately after each choice, without knowing which choice comes next), and in an experiment with N choices pay all choices but multiplied by 1/N to get average, and not very large total payment. Take as gold standard OT (one task), something that for instance Birnbaum (1992) took issue with. Find that repeated payments (which suffer from income effects) do best in the sense of staying closest to OT. Sections 3.2 & 9.1 & 10.1 suggest that the RIS (they write POR) is not incentive compatible if expected utility is violated, such as under RDU and PT. But the counterexamples make particular assumptions about dynamic decisions and reduction. It is possible to have incentive compatibility for RIS and nonEU under particular other dynamic decision principles, e.g. backward induction. Cohen, Jaffray, & Said (1987) use the term isolation for such cases. Bardsley et al. (2010 p. 269) points this out too. Section 11 cites the working paper Harrison & Swarthout (2013), later appeared in 2014, affirmatively on this point, but the Harrison & Swarthout paper is a weak one to side with. §6 1st sentence strangely writes: “It has been argued in the literature (e.g., Kahneman and Tversky 1979) that subjects evaluate each choice independently of the other choice opportunities in an experiment.” I cannot imagine that Kahneman and Tversky would ever write such a weird universal claim, with violations shown for instance in Redelmeier, Donald A. & Amos Tversky (1992) “On the Framing of Multiple Prospects,” Psychological Science 3, 191–193. Section 9.1 incorrectly claims that using the RIS (thye write POR) is incompatible with nonEU theories such as PT (they write CPT). I discussed this point above. It also incorrectly writes that PT would assume independence of wealth level. §11 writes: “there is no known “ideal mechanism” that will solve all the problems we describe.” %} Cox, James C., Vjollca Sadiraj, & Ulrich Schmidt (2015) “Paradoxes and Mechanisms for Choice under Risk,” Experimental Economics 18, 215–250. {% DOI: HTTP://DX.DOI.ORG/10.1371/journal.pone.0090742 random incentive system: imagine a risky choice between S and R. But it is preceded by a risky choice between S´ and R´ where R´ is superior to R and S´ is inferior to S (the preceding choice is called risky-dominating). The preceding choice will move choices between R and S in the direction of S, violating the isolation condition of RIS. %} Cox, James C., Vjollca Sadiraj, & Ulrich Schmidt (2014) “Asymmetrically Dominated Choice Problems, the Isolation Hypothesis and Random Incentive Mechanisms,” PLoS ONE 9, e90742. {% Test the St. Petersburg paradox. %} Cox, James C., Vjollca Sadiraj, & Bodo Vogt (2011) “On the Empirical Relevance of St. Petersburg Lotteries,” working paper. {% %} Cox, James C., Vjollca Sadiraj, Bodo Vogt, & Utteeyo Dasgupta (2013) “Is there a Plausible Theory for Risky Decisions? A Dual Calibration Critique,” Economic Theory 54, 305–333. {% %} Cox, James C., Vernon L. Smith, & James M. Walker (1985) “Experimental Development of Sealed-Bid Auction Theory; Calibrating Controls for Risk Aversion,” American Economic Review 75, 160–165. {% anonymity protection %} Cox, Lawrence H., Sarah-Kathryn McDonald, & Dawn Nelson (1986) “Confidentiality Issues at the United States Bureau of the Census,” Journal of Official Statistics 2, 135–160. {% A very didactical explanation that mean-variance can violate stochastic dominance. %} Cox, Jr, Louis Anthony (2008) “Why Risk Is not Variance: An Expository Note,” Risk Analysis 28, 925–928. {% %} Cox, Richard T. (1946) “Probability, Frequency, and Reasonable Expectation,” American Journal of Physics 14, 1–13. {% This paper discusses the role of preference foundations, i.e., preference axiomatizations, i.e., representation theorems. In particular, it considers the role of theoretical terms there. And then, the semantic role of giving meaning to those terms. P. 293: “Finally, the few explanations that have been offered as to why these results are so important sometimes reflect doctrines that have been largely abandoned in philosophy of science and in philosophy of language (notably operationalism and behaviorism).” My opinion is a what the paper calls “anti-holist attitude towards meaning.” Preference foundations only show what the assumed existence (specifying also the decision theory, e.g., EU) means, not entirely the terms themselves. It is only part of the meaning. Showing how to measure them, which is something that particular proofs do (I always try to write my proofs this way), operationalizes them, which adds to their meaning. P. 297 nicely relates to theoretical terms in natural sciences, such as electrons or genes. For this typical existence of subjective parameters in preference foundations I cannot think of an analog in natural sciences. P. 297 3rd para: “The problem of the meaning of theoretical concepts is usually presented as follows: one assumes that theory T is formulated in a certain language, as a set of propositions, and that one can distinguish, in one’s conceptual repertoire, between two categories of terms. In the neo-positivist tradition, theoretical terms are contrasted with observational terms, where a term is considered observational when you can determine through observation whether or not it applies to an entity in its domain of application. Lewis (1970, 1972) liberalizes the distinction: the ‘theoretical’ terms are terms that are introduced by a theory T, and they are contrasted with terms whose meaning was determined prior to the theory T. For the discussion here, there is no need to decide between these distinctions. As standard, we will use the word t-terms to designate theoretical terms, and o-terms to designate observational terms or those introduced prior to the theory T.” P. 297 last para: “Theoretical terms can be explicitly defined through observables, although usually this is complex, but mostly this is not done and the meaning is left implicit. The authors cite Ramsey (1929) and Carnap (1959), taking the RCL (Ramsey-Carnap-Lewis) approach. It takes theoretical terms as implicitly simultaneously defined in a theory. Lewis defines every single theoretical term through the existence of all the other theoretical terms such that the theory considered holds. This is close to the existence sentences in behavioral foundations. P. 300 bottom seems to suggest that Lewis’ definition may solve some philosophical problems but is trivial as regards its clarification of representation theorems. The main alternative is the causal-historical theory (p. 298 middle). It is something like through causal relations, but I did not understand. CRL fits best with decision theory. P. 299 middle: “given the affinities between decision-theoretic and folk-psychological concepts (for example, between subjective probability and belief or between utility and desire), it may be asked to what extent the concepts used by decision theorists are truly theoretical terms, rather than (pre-existing) ordinary language terms. However, there are reasons to suspect that an objection along these lines is flawed. As Enç (1976) has pointed out in his discussion of similar examples from the natural sciences, there is a difference between terms such as ‘heat’ and ‘magnet’ on the one hand and ‘caloric’ or ‘magnetic field’ on the other.” P. 299-300 (conservation of influence): “First, this way of defining subjective utility and probability is very similar to the way in which, in the philosophy of mind, functionalists (such as Lewis himself) characterize ordinary beliefs and desires. More exactly the definitions are similar to forward-looking features in the characterization of mental states, i.e. features that refer to their effects, in contrast with backward-looking features, which refer to their causes.” Unfortunately, the paper does not elaborate on this point. Download 7.23 Mb. Share with your friends:
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